ML Engineer
Core
Building and scaling production infrastructure, training pipelines, and experimentation platforms for large-scale autonomous AI systems used in scientific discovery.
Role type
Senior ML Engineer (Systems & Infrastructure)
Builds
Training pipelines, experimentation platforms, data pipelines, and deployment systems for large-scale LLMs.
Domain
AI for Science / Biotech / Pharma
Deliverable
production ML models
Required skills
Large-scale ML system design, distributed training, data pipeline engineering, system observability, model deployment, orchestration, debugging, PyTorch/JAX fluency, systems thinking.
Preferred skills
Experience with autonomous AI agents, long-horizon reasoning systems, end-to-end model training.
Technologies
PyTorch, JAX, large-scale distributed systems.
Responsibilities
Building and scaling training pipelines for large-scale LLM systems, developing experimentation platforms for fast iteration, designing data pipelines for observability and reproducibility, improving training run orchestration and monitoring, supporting model deployment and inference, translating scientific problems into production systems.
Seniority
Senior, hands-on IC
